1. UKM Learning and Research Repository
  2. Journal Article / Artikel Jurnal
  3. Journal Content Pages/ Kandungan Halaman Jurnal
Please use this identifier to cite or link to this item: https://ptsldigital.ukm.my/jspui/handle/123456789/578854
Full metadata record
DC FieldValueLanguage
dc.contributor.authorAbdul Rauf Abdul Rasam (USM)
dc.contributor.authorNoresah Mohd Shariff (UITM)
dc.contributor.authorJiloris F. Dony
dc.contributor.authorPunitha Makeswaran
dc.date.accessioned2023-11-06T03:09:03Z-
dc.date.available2023-11-06T03:09:03Z-
dc.date.issued2017-01
dc.identifier.issn0128-7702
dc.identifier.otherukmvital:116267
dc.identifier.urihttps://ptsldigital.ukm.my/jspui/handle/123456789/578854-
dc.descriptionDeveloping a model to map tuberculosis (TB) cases in Malaysia for boosting early detection is vital. A knowledge-driven geographical information system (GIS) modelling is an alternative approach developed for assessing potential risk areas of TB at Section 17, Shah Alam, Selangor. It is a weight-rating score model and spatial multi-criteria decision making (MCDM) method for producing a ranked map based on the index values and risk indicators with a five-score scale. Results showed 34.85% of the study areas are potential TB high risk zones, ranging from medium to very high risk. This is consistent with the findings obtained from overlay comparison with the current cases in 2015.The TB risk map and validation indicated a reasonable match with areas considered as potential TB risk areas, particularly in urban and crowded environments. Thus, a GIS-based MCDM technique can be applied in the national TB screening and monitoring programme.
dc.language.isoen
dc.publisherUniversiti Putra Malaysia Press
dc.relation.haspartPertanika Journals
dc.relation.urihttp://www.pertanika.upm.edu.my/regular_issues.php?jtype=3&journal=JSSH-25-S-1
dc.rightsUKM
dc.subjectDisease mapping
dc.subjectKnowledge-driven GIS model
dc.subjectSpatial MCDM
dc.subjectRisk area
dc.subjectTuberculosis
dc.titleMapping risk areas of tuberculosis using knowledge-driven gis model in Shah Alam, Malaysia
dc.typeJournal Article
dc.format.volume25
dc.format.pages135-144
dc.format.issueSpecial Issue
Appears in Collections:Journal Content Pages/ Kandungan Halaman Jurnal

Files in This Item:
File Description SizeFormat 
ukmvital_116267+Source01+Source010.PDF627.18 kBAdobe PDFThumbnail
View/Open
Show simple item record Recommend this item


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.